<html>
<head>
<title>
Netlab Reference Manual mdngrad
</title>
</head>
<body>
<H1> mdngrad
</H1>
<h2>
Purpose
</h2>
Evaluate gradient of error function for Mixture Density Network.

<p><h2>
Synopsis
</h2>
<PRE>

g = mdngrad(net, x, t)
</PRE>


<p><h2>
Description
</h2>

<CODE>g = mdngrad(net, x, t)</CODE> takes a mixture density network data
structure <CODE>net</CODE>, a matrix <CODE>x</CODE> of input vectors and a matrix
<CODE>t</CODE> of target vectors, and evaluates the gradient <CODE>g</CODE> of the
error function with respect to the network weights. The error function
is negative log likelihood of the target data.  Each row of <CODE>x</CODE>
corresponds to one input vector and each row of <CODE>t</CODE> corresponds to
one target vector.

<p><h2>
See Also
</h2>
<CODE><a href="mdn.htm">mdn</a></CODE>, <CODE><a href="mdnfwd.htm">mdnfwd</a></CODE>, <CODE><a href="mdnerr.htm">mdnerr</a></CODE>, <CODE><a href="mdnprob.htm">mdnprob</a></CODE>, <CODE><a href="mlpbkp.htm">mlpbkp</a></CODE><hr>
<b>Pages:</b>
<a href="index.htm">Index</a>
<hr>
<p>Copyright (c) Ian T Nabney (1996-9)
<p>David J Evans (1998)

</body>
</html>